7258 Open source projects that are alternatives of or similar to Deep Learning Time Series

Bitcoin price Prediction ( Time Series ) using LSTM Recurrent neural network

Anomaly detection for temporal data using LSTMs

PyTorch tutorial for learners

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Application of machine learning to the Coinbase (GDAX) orderbook

Time Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

Image Captioning: Implementing the Neural Image Caption Generator with python

Named Entity Recognition using multilayered bidirectional LSTM

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

How to build RNNs and LSTMs from scratch with NumPy.

Some of the ML and DL related reading materials, research papers that I've read

Keras tutorial for beginners (using TF backend)

Deep Learning based Automatic Speech Recognition with attention for the Nvidia Jetson.

A Keras library for multi-step time-series forecasting.

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction

A Natural Language Toolkit for Indian Languages

The Official Deep Learning Framework for Route-based Place Recognition

Sentiment Analysis on the First Republic Party debate in 2016 based on Python,NLTK and ML.

Neural machine translator for English2German translation.

Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Implementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Using LSTM network for time series forecasting

Stock Price Prediction using Machine Learning Techniques

Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

📃 **Unofficial** PyTorch Implementation of DA-RNN (arXiv:1704.02971)

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

Image Captioning using InceptionV3 and beam search

This repository helps you understand python from the scratch.

Data Augmentation by Backtranslation (DAB) ヽ( •_-)ᕗ

An open-source, low-code machine learning library in Python

Sentence paraphrase generation at the sentence level

Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"

Transformer of "Attention Is All You Need" (Vaswani et al. 2017) by Chainer.

A stock trading bot that uses machine learning to make price predictions.

VDSR (CVPR2016) pytorch implementation

Anomaly detection implemented in Keras

Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

Implementation of a hierarchical CNN based model to detect Big Five personality traits

DeltaPy - Tabular Data Augmentation (by @firmai)

Deep Learning Projects that Build Themselves

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

Action recognition using soft attention based deep recurrent neural networks

Reinforcement Learning for Portfolio Management

Synthetic Data Generation for tabular, relational and time series data.

RMDL: Random Multimodel Deep Learning for Classification

This is an open sourced book on deep learning.

Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP

Cryptocurrency Price Prediction Using LSTM neural network